Search results for: brain machine interface (BMI)

Authors: Luxi Chen

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The land finance in China in recent years has propelled urban renewals in the name of historical conservation and led to massive gentrification and compulsory relocation. Such inequalities cause insurgence. Drawing on public planning information, ethnographic field notes, and online interview data about Guangzhou's Enninglu Area, this paper aims to present how such insurgence has been contained and put down gradually through depoliticization narratives represented by "improving living conditions," "conserving historical culture," and "public participation”. This paper's findings include that 1) Besides economic growth, maintaining social stability in alignment with the central government are equally important to local government, reveals the latter efforts to mediate the growth coalition, residents, media, and academics so as to reconstruct the interface between state and society; 2) To empower the insurgence, the media and academics use public interests for propaganda, that diverts attention away from its political dimension; 3) In response, the government introduces improved regulations and planning, turning social inequalities into technical inadequacy so as to become the defender of public interests, which justifies the incoming renewal and prevents public questioning. By comparing regime changes among governments, developers, residents, media, and academics caused by renewal policies, this paper presents the depoliticized narrative as a counter-insurgence strategy to contain social conflicts and to boost inner-city renewal.

Keywords: inner city renewal, depoliticization, historical conservation, public participation

Procedia PDF Downloads 220

Authors: Alex Kiselyov, Suehyun Cho, Darrell Harrington; Florent Cros, Olin Palmer, John Caputo, Michael Kardosh, Eran Oren, William Loudon, Michael Shpigelmacher

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Despite the most aggressive surgical and adjuvant therapeutic strategies, treatment of both pediatric and adult brainstem tumors remains problematic. Novel strategies, including targeted biologics, immunotherapy, and specialized delivery systems such as convection-enhanced delivery (CED), have been proposed. While some of these novel treatments are entering phase I trials, the field is still in need of treatment(s) that exhibits dramatically enhanced potency with optimal therapeutic ratio. Bionaut Labs has developed a modular microrobotic platform for performing localized delivery of diverse therapeutics in vivo. Our biocompatible particles (Bionauts™) are externally propelled and visualized in real-time. Bionauts™ are specifically designed to enhance the effect of radiation therapy via anatomically precise delivery of a radiosensitizing agent, as exemplified by temozolomide (TMZ) and Avastin™ to the brainstem gliomas of diverse origin. The treatment protocol is designed to furnish a better therapeutic outcome due to the localized (vs systemic) delivery of the drug to the neoplastic lesion(s) for use as a synergistic combination of radiation and radiosensitizing agent. In addition, the procedure is minimally invasive and is expected to be appropriate for both adult and pediatric patients. Current progress, including platform optimization, selection of the lead radiosensitizer as well as in vivo safety studies of the Bionauts™ in large animals, specifically the spine and the brain of porcine and ovine models, will be discussed.

Keywords: Bionaut, brainstem, glioma, local delivery, micro-robot, radiosensitizer

Procedia PDF Downloads 180

Authors: Eva Savy, Anthony Ruiz

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In extrusion blow molding, there is great variability in product quality due to the sensitivity of the machine settings. These variations lead to unnecessary rejects and loss of time. Yet production control is a major challenge for companies in this sector to remain competitive within their market. Current quality control methods only apply to finished products (vision control, leak test...). It has been shown that material melt temperature, blowing pressure, and ambient temperature have a significant impact on the variability of product quality. Since blowing is a key step in the process, we have studied this parameter in this paper. The objective is to determine if airflow analysis allows the identification of quality problems before the full completion of the manufacturing process. We conducted tests to determine if it was possible to identify a leakage defect and an obstructed defect, two common defects on products. The results showed that it was possible to identify a leakage defect by airflow analysis.

Keywords: extrusion blow molding, signal, sensor, defects, detection

Procedia PDF Downloads 126

Authors: V. Rashtchi, H. Bizhani, F. R. Tatari

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This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a trade off between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.

Keywords: induction machine, loss minimization, magnetizing current, particle swarm optimization

Procedia PDF Downloads 621

Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

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Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

Procedia PDF Downloads 277

Authors: Chong-Yang Qiao

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Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.

Keywords: mobile augmented reality, remote collaboration, user experience, cognition model

Procedia PDF Downloads 184

Authors: B. Arzhanov, A. Correia, P. Delgado, J. Meireles

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Due to the higher power loss levels in electronic components, the thermal design of PCBs (Printed Circuit Boards) of an assembled device becomes one of the most important quality factors in electronics. Nonetheless, some of leading causes of the microelectronic component failures are due to higher temperatures, the leakages or thermal-mechanical stress, which is a concern, is the reliability of microelectronic packages. This article presents an experimental approach to measure the junction temperature of exposed pad packages. The implemented solution is in a prototype phase, using a temperature-sensitive parameter (TSP) to measure temperature directly on the die, validating the numeric results provided by the Mechanical APDL (Ansys Parametric Design Language) under same conditions. The physical device-under-test is composed by a Thermal Test Chip (TTC-1002) and assembly in a QFN cavity, soldered to a test-board according to JEDEC Standards. Monitoring the voltage drop across a forward-biased diode, is an indirectly method but accurate to obtain the junction temperature of QFN component with an applied power range between 0,3W to 1.5W. The temperature distributions on the PCB test-board and QFN cavity surface were monitored by an infra-red thermal camera (Goby-384) controlled and images processed by the Xeneth software. The article provides a set-up to monitorize in real-time the junction temperature of ICs, namely devices with the exposed pad package (i.e. QFN). Presenting the PCB layout parameters that the designer should use to improve thermal performance, and evaluate the impact of voids in solder interface in the device junction temperature.

Keywords: quad flat no-Lead packages, exposed pads, junction temperature, thermal management and measurements

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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For security purposes, it is important to detect passwords entered by unauthorized users. With traditional alphanumeric passwords, if the content of a password is acquired and correctly entered by an intruder, it is impossible to differentiate the password entered by the intruder from those entered by the authorized user because the password entries contain precisely the same character set. However, no two entries for the gesture-based passwords, even those entered by the person who created the password, will be identical. There are always variations between entries, such as the shape and length of each stroke, the location of each stroke, and the speed of drawing. It is possible that passwords entered by the unauthorized user contain higher levels of variations when compared with those entered by the authorized user (the creator). The difference in the levels of variations may provide cues to detect unauthorized entries. To test this hypothesis, we designed an empirical study, collected and analyzed the data with the help of machine-learning algorithms. The results of the study are significant.

Keywords: authentication, gesture-based passwords, shoulder-surfing attacks, usability

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Authors: Ghada S. Moussa

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Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.

Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm

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Authors: Mardiati Zain, Yetti Marlida, Elihasridas Elihasridas, Erpomen Erpomen, Andri Andri

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Background: Livestock productivity is greatly influenced by the energy and protein balance in diet. This study aimed to determine the energy and protein balance of male Simenthal cattle diet with protein and energy levels. The experimental design used was a randomized block design (RBD) 2x3x3 factorial design. There are two factors namely A level of energy diet that is 65% and 70% TDN. Factor B is a protein level of diet used were 10, 12 and 14% and each treatment is repeated three times. The weight of Simenthal cattle used ranged between 240 - 300 kg. Diet consisted of ammoniated rice straw and concentrated with ratio 40:60. Concentrate consisted of palm kernel cake, rice brain, cassava, mineral, and urea. The variables measured were digestibility of dry matter, organic matter and fiber, dry matter intake, daily gain, feed efficiency and blood characteristic. Results: There was no interaction between protein and energy level of diet on the nutrients intake (DM intake, OM intake, CP intake), weight gain and efficiency (P < 0.01). There was an interaction between protein and energy level of diet on digestibility (DM, OM, CP and allantoin urine (P > 0.01) Nutrients intake decreases with increasing levels of energy and protein diet, while nutrient digestibility, Avarage daily gain and feed efficiency increases with increasing levels of energy and protein diet. Conclusions: The result can be concluded that the best treatment was A2B1 which is energy level 70% TDN and protein 10%, where are dry matter intake 7.66 kg/d, daily gain 1.25 kg/d, feed efficiency 16.12%, and dry matter and organic matter digestibility 64.08 and 69.42% respectively.

Keywords: energy and protein ratio, simenthal cattle, rice straw ammoniated, digestibility

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Authors: Joo Min Kim, Dongyoun Shin

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The project Future Station (FS) seek for a deeper understanding of metro station. The main idea of the project is enhancing the underground environment by combining new architectural design with IoT technology. This research shows the understanding of the metro environment giving references regarding traditional design approaches and IoT combined space design. Based on the analysis, this research presents design alternatives in two metro stations those are chosen for a testbed. It also presents how the FS platform giving a response to travelers and deliver the benefit to metro operators. In conclusion, the project describes methods to build future metro service and platform that understand traveler’s intentions and giving appropriate services back for enhancing travel experience. It basically used contemporary technology such as smart sensing grid, big data analysis, smart building, and machine learning technology.

Keywords: future station, digital lifestyle experience, sustainable metro, smart metro, smart city

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Authors: Rajveer, Abhinav Saxena, Sanjeev Das

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The study is focused on the strength of forged aluminum alloy (AA) 6082 (T6). Aluminum alloy 6082 belongs to Al-Mg-Si family which has a wide range of automotive applications. A decrease in the strength of AA 6082 alloy was observed after T6 treatment. The as-received (extruded), forged, and forged + heat treated samples were examined to understand the reason. These examinations were accomplished by optical (OM) and scanning electron microscope (SEM) and X-ray diffraction (XRD) studies. It was observed that the defects had an insignificant effect on the alloy strength. The alloy samples were subjected to age hardening treatment and the time to achieve peak hardening was acquired. Standard tensile specimens were prepared from as-received (extruded), forged, forged + solutionized and forged + solutionized + age hardened. Tensile tests were conducted by Instron universal testing machine. It was observed that there was a significant drop in tensile strength in the case of solutionized sample. The detailed study of the fracture samples showed that the solutionizing after forging was not the best way to increase the strength of Al 6082 alloy.

Keywords: aluminum alloy 6082, strength, forging, age hardening

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Authors: Hafiz Muhammad Adeel Sharif, Tian Li, Changping Li

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Recently, the emission of nitrogen-sulphur oxides (NOₓ, SO₂) has become a global issue and causing serious threats to health and the environment. Catalytic reduction of NOx and SOₓ gases into friendly gases is considered one of the best approaches. However, regeneration of the catalyst, higher bond-dissociation energy for NOx, i.e., 150.7 kcal/mol, escape of intermediate gas (N₂O, a greenhouse gas) with treated flue-gas, and limited activity of catalyst remains a great challenge. Here, a cheap, binderless naturally-extracted bass-wood thin carbon electrode (TCE) is presented, which shows excellent catalytic activity towards NOx reduction. The bass-wood carbonization at 900 ℃ followed by thermal activation in the presence of CO2 gas at 750 ℃. The thermal activation resulted in an increase in epoxy groups on the surface of the TCE and enhancement in the surface area as well as the degree of graphitization. The TCE unique 3D strongly inter-connected network through hierarchical micro/meso/macro pores that allow large electrode/electrolyte interface. Owing to these characteristics, the TCE exhibited excellent catalytic efficiency towards NOx (~83.3%) under ambient conditions and enhanced catalytic response under pH and sulphite exposure as well as excellent stability up to 168 hours. Moreover, a temperature-dependent activity trend was found where the highest catalytic activity was achieved at 80 ℃, beyond which the electrolyte became evaporative and resulted in a performance decrease. The designed electrocatalyst showed great potential for effective NOx-reduction, which is highly cost-effective, green, and sustainable.

Keywords: electrocatalyst, NOx-reduction, bass-wood electrode, integrated wet-scrubbing, sustainable

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Authors: Ching Yern Chee

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Various loading of nano silica is added into polyurethane (PU) and then coated on porcelain substrate. The wear and friction properties of the porcelain substrates coated with polyurethane/nano silica nano composite coatings were investigated using the reciprocating wear testing machine. The friction and wear test of polyurethane/nano silica coated porcelain substrate was studied at different sliding speed and applied load. It was found that the optimum composition of nano silica is 3 wt% which gives the lowest friction coefficient and wear rate in all applied load ranges and sliding speeds. For 3 wt% nano silica filled PU coated porcelain substrate, the increment of sliding speed caused higher wear rates but lower frictions coefficient. Besides, the friction coefficient of nano silica filled PU coated porcelain substrate decreased but the wear rate increased with the applied load.

Keywords: porcelain, nanocomposite coating, morphology, friction, wear behavior

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Authors: Ajmal Hussain

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In Indian music parlance, Rasa denotes a distinct aesthetic experience that builds up in the mind of the listeners while listening to a piece of Indian classical music. The distinction of the experience is rooted in the concept that it gives rise to an enhanced awareness about the Self or God and creates a mental state detached from mundane issues of everyday life. The theory of Rasa was initially proposed in the context of theatre but became a part of Indian musicological discourse roughly two thousand years ago, however, to this day, it remains shrouded in mystery due to its religious associations and connotations. This paper attempts to demystify the theory of Rasa in the light of available scientific knowledge fund particularly in Brain and Mind sciences. The paper initially describes the religious context of the theory of Rasa and then discusses its classical formulations by Bharata and Abhinavagupta including the steps and stages laid down by the latter to explain the creation of musical experience. The classical formulations are then interpreted with reference to the scientific knowledge fund about the human mind and mechanics of perception. The study uses the model of human mind as proposed by Portuguese-American neuroscientist Antonio Damasio in his theory ‘A Nesting Principle’. On the basis of the findings by Damasio, the paper interprets the experience of Rasa from a scientific perspective and clarifies the sequence of steps and stages involved in the making of musical experience. The study concludes that although the classical formulations of Rasa identify key aspects of musical experience, the association of Rasa with religion is misleading. The association with religion does not depend upon musical stimulus but the intellectual orientation of the listener. It further establishes that the function of Rasa is more profound as, from an evolutionary perspective, it can be seen as a catalyst for higher consciousness.

Keywords: aesthetic, consciousness, music, Rasa

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Authors: Angela Luft, Sebastian Bremen, Nicolae Balc

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Additive manufacturing processes have entered large parts of the industry and their range of application have progressed and grown significantly in the course of time. A major advantage of additive manufacturing is the innate flexibility of the machines. This corelates with the ongoing demand of creating highly flexible production environments. However, the potential of additive manufacturing technologies to enhance the flexibility of production systems has not yet been truly considered and quantified in a systematic way. In order to determine the potential of additive manufacturing technologies with regards to the strategic flexibility design in production systems, an integrated evaluation model has been developed, that allows for the simultaneous consideration of both conventional as well as additive production resources. With the described model, an operational scope of action can be identified and quantified in terms of mix and volume flexibility, process complexity, and machine capacity that goes beyond the current cost-oriented approaches and offers a much broader and more holistic view on the potential of additive manufacturing. A respective evaluation model is presented this paper.

Keywords: additive manufacturing, capacity planning, production systems, strategic production planning, flexibility enhancement

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Authors: Jimmy Jiun-Ming Su, Yuan-Min Lin

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Bioprinting has been applied to produce 3D cellular constructs for tissue engineering. Microextrusion printing is the most common used method. However, printing low viscosity bioink is a challenge for this method. Herein, we developed a new 3D printing system to fabricate cell-laden hydrogels via a DLP-based projector. The bioprinter is assembled from affordable equipment including a stepper motor, screw, LED-based DLP projector, open source computer hardware and software. The system can use low viscosity and photo-polymerized bioink to fabricate 3D tissue mimics in a layer-by-layer manner. In this study, we used gelatin methylacrylate (GelMA) as bioink for stem cell encapsulation. In order to reinforce the printed construct, surface modified hydroxyapatite has been added in the bioink. We demonstrated the silanization of hydroxyapatite could improve the crosslinking between the interface of hydroxyapatite and GelMA. The results showed that the incorporation of silanized hydroxyapatite into the bioink had an enhancing effect on the mechanical properties of printed hydrogel, in addition, the hydrogel had low cytotoxicity and promoted the differentiation of embedded human bone marrow stem cells (hBMSCs) and retinal pigment epithelium (RPE) cells. Moreover, this bioprinting system has the ability to generate microchannels inside the engineered tissues to facilitate diffusion of nutrients. We believe this 3D bioprinting system has potential to fabricate various tissues for clinical applications and regenerative medicine in the future.

Keywords: bioprinting, cell encapsulation, digital light processing, GelMA hydrogel

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Authors: Pascal Horni, Sandro Fuchs

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In presence of increasing deficits and public debt among OECD countries, the debate on fiscal disciple and mechanisms to constrain public spending policy heated up and gave rise to the institutionalization of fiscal rules. Considering the notions from political economy literature and the therein advocated axiom of maximization of votes, introduction of institutional mechanisms and rules to govern public spending is likely to be coined by electoral motives. While there exists a series of research concerned with the rise of creative accounting in the presence fiscal rules, implementation of accrual government accounting and its impact on the biting of fiscal rules has to authors’ best knowledge never been explored. This paper serves the illumination of the connection between debt break mechanisms and the adoption of accrual public sector accounting standards such as the IPSAS in the interface of political economy in the Swiss context. By explicitly considering the technical accounting dimension, this paper develops an integrated conceptual view on well-established Public Financial Management (PFM) institutions and elaborates how their interdependencies can co-create value with regard to the contemporary challenge of fiscal sustainability. Derivation of this integrated view follows an explorative approach, taking into account expert interviews with director level staff from cantonal finance administrations and policy documents, as well as literature from both research areas – public sector accounting and political economy.

Keywords: accounting, fiscal rules, International Public Sector Accounting Standards (IPSAS), public financial management

Procedia PDF Downloads 147

Authors: Yun-Xuan Tang, Pei-Yuan Liu, Kun-Mu Lu, Min-Tsung Tseng, Liang-Kuang Chen, Yuh-Feng Tsai, Ching-Wen Lee, Jay Wu

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Breast cancer is predominant of malignant tumors in females. The increase in the glandular density increases the risk of breast cancer. BI-RADS is a frequently used density indicator in mammography; however, it significantly overestimates the glandularity. Therefore, it is very important to accurately and quantitatively assess the glandularity by mammography. In this study, 20%, 30% and 50% glandularity phantoms were exposed using a mammography machine at 28, 30 and 31 kVp, and 30, 55, 80 and 105 mAs, respectively. The regions of interest (ROIs) were drawn to assess the gray level. The relationship between the glandularity and gray level under various compression thicknesses, kVp, and mAs was established by the multivariable linear regression. A phantom verification was performed with automatic exposure control (AEC). The regression equation was obtained with an R-square value of 0.928. The average gray levels of the verification phantom were 8708, 8660 and 8434 for 0.952, 0.963 and 0.985 g/cm3, respectively. The percent differences of glandularity to the regression equation were 3.24%, 2.75% and 13.7%. We concluded that the proposed method could be clinically applied in mammography to improve the glandularity estimation and further increase the importance of breast cancer screening.

Keywords: mammography, glandularity, gray value, BI-RADS

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the e-learning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery

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Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies

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With the world climate projected to warm and major cities in developing countries becoming increasingly populated and polluted, governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of an adaptable model of these risks. Simulations are performed using the EnergyPlus building physics software. An accurate metamodel is formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) are compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.

Keywords: neural networks, radial basis functions, metamodelling, python machine learning libraries

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Authors: Wenqing Fan, Yixuan Cheng, Wei Huang

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The diversity and complexity of modern IT systems make it almost impossible for internal teams to find vulnerabilities in all software before the software is officially released. The emergence of threat intelligence and vulnerability reporting policy has greatly reduced the burden on software vendors and organizations to find vulnerabilities. However, to prove the existence of the reported vulnerability, it is necessary but difficult for security incident response team to build a deliberated vulnerable environment from the vulnerability report with limited and incomplete information. This paper presents a structured, standardized, machine-oriented vulnerability intelligence format, that can be used to automate the orchestration of Deliberated Vulnerable Environment (DVE). This paper highlights the important role of software configuration and proof of vulnerable specifications in vulnerability intelligence, and proposes a triad model, which is called DIR (Dependency Configuration, Installation Configuration, Runtime Configuration), to define software configuration. Finally, this paper has also implemented a prototype system to demonstrate that the orchestration of DVE can be automated with the intelligence.

Keywords: DIR triad model, DVE, vulnerability intelligence, vulnerability recurrence

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Authors: Marcin Michalak

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Due to the increasing efforts on saving our natural environment a change in the structure of energy resources can be observed - an increasing fraction of a renewable energy sources. In many countries traditional underground coal mining loses its significance but there are still countries, like Poland or Germany, in which the coal based technologies have the greatest fraction in a total energy production. This necessitates to make an effort to limit the costs and negative effects of underground coal mining. The longwall complex is as essential part of the underground coal mining. The safety and the effectiveness of the work is strongly dependent of the diagnostic state of powered roof supports. The building of a useful and reliable diagnostic system requires a lot of data. As the acquisition of a data of any possible operating conditions it is important to have a possibility to generate a demanded artificial working characteristics. In this paper a new approach of modelling a leg pressure in the single unit of powered roof support. The model is a result of the analysis of a typical working cycles.

Keywords: machine modelling, underground mining, coal mining, structure

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Authors: S. Brain, P. J. Storer, H. Strydom, Z. M. Solaiman

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Increasing farmer awareness of soil health, the impact of agricultural management practices, and the requirement for high-quality agricultural produce are major factors driving the rapid adoption of biological seed treatments - currently valued globally at USD 1.5 billion. Biological seed coatings with multistrain plant beneficial microbial technology have the capability to affect plant establishment, growth, and development positively. These beneficial plant microbes can potentially increase soil health, plant yield, and nutrition – acting as bio fertilisers, rhizoremediators, phytostimulators, and stress modulators, and can ultimately reduce the overall use of agrichemicals. A field trial was conducted on MACE wheat in the central wheat belt of Western Australia to evaluate a proprietary seed coating technology (Langleys Bio-EnergeticTM Microbe blend (BMB)) on a conventional program (+/- BMB microbes) and a Regenerative Biomineral fertiliser program (+/- BMB microbes). The Conventional (+BMB) and Biomineral (+BMB) treated plants had no fungicide treatments and had no disease issues. Control (No fertiliser, No microbes), Conventional (No Microbes), and Biomineral (No Microbes) were treated with fungicides (seed dressing and foliar). From the research findings, compared to control and no microbe treatments, both the Conventional (+ BMB) and Biomineral (+ BMB) showed significant increases in Soil Carbon (SOC), Seed germination, nutrient use efficiency (NUE) of nitrogen, phosphate and mineral nutrients, grain mineral nutrient uptake, protein %, hectolitre weight, and fewer screenings, yield, and gross margins.

Keywords: biological seed coating, biomineral fertiliser, plant nutrition, regenerative and conventional agriculture

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Authors: Anderson Rocha, Pedro Miguel de Figueiredo Dinis Oliveira Gaspar

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Machine vision has been widely used in recent years in agriculture, as a tool to promote the automation of processes and increase the levels of productivity. The aim of this work is the development of a path recognition algorithm based on image processing to guide a terrestrial robot in-between tree rows. The proposed algorithm was developed using the software MATLAB, and it uses several image processing operations, such as threshold detection, morphological erosion, histogram equalization and the Hough transform, to find edge lines along tree rows on an image and to create a path to be followed by a mobile robot. To develop the algorithm, a set of images of different types of orchards was used, which made possible the construction of a method capable of identifying paths between trees of different heights and aspects. The algorithm was evaluated using several images with different characteristics of quality and the results showed that the proposed method can successfully detect a path in different types of environments.

Keywords: agricultural mobile robot, image processing, path recognition, hough transform

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Authors: Sulyman Abdulhakeem Olarewaju, S. O. Malomo, M. T. Yakubu, J. O. Akolade

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The ameliorative effect of Celosia argentea var. cristata leaf extract against cadmium (Cd) induced oxidative stress and toxicity in selected tissues of rats was investigated. Toxicity coupled with oxidative stress was induced in rats by oral administration of Cd (8 mg/kg b. wt). Preliminary quantitative phytochemical and in vitro antioxidant analyses showed that the methanolic extract of C. argentea leaves was constituted by polyphenols (5.72%), saponins (3.20%), tannins (0.65%) and cadenolides (0.006%). IC50 of 9800, 7406, and 45.04 μg/ml were recorded for inhibition of linoleic acid oxidation, 2, 2-diphenyl-1-picrylhydrazyl and hydrogen peroxide radicals respectively. Simultaneous administration of C. argentea leaf extract with Cd significantly attenuated Cd-induced elevation of serum enzyme markers such as aspartate and alanine transaminase, alkaline and acid phosphatase as well as γ-glutaryltransferase in a dose-dependent fashion, while their reduced level in the liver were significantly increased. Higher levels of enzymatic antioxidants; superoxide dismutase and catalase activities were observed in the liver, brain, kidney and testes of the Cd-induced rats treated with C. argentea extract, while lipid peroxidation expressed in malondialdehyde concentrations were lower when compared to values in rats administered Cd only. Other Cd-induced toxicity and stress markers in the serum viz. reduced uric acid and albumin levels as well as elevated total and unconjugated bilirubin were attenuated by the extract and their values compared favorably with those animals co-administered cadmium with ascorbic acid. Data from the study showed that oral administration of extract from the leaf C. argentea may ameliorate Cd-induced oxidative stress and toxicity in rats.

Keywords: toxicity, cadmium, celosia, antioxidants, oxidative stress

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Authors: Marvin Chibuzo Offiah, Susanne Rosenthal, Markus Borschbach

Abstract:

Certain research projects in Computer Science often involve research on existing signal processing algorithms and developing improvements on them. Research budgets are usually limited, hence there is limited time for implementing the algorithms from scratch. It is therefore common practice, to use implementations provided by other researchers as a template. These are most commonly provided in a rapid development, i.e. 4th generation, programming language, usually Matlab. Rapid development is a common method in Computer Science research for quickly implementing and testing new developed algorithms, which is also a common task within agile project organization. The growing relevance of mobile devices in the computer market also gives rise to the need to demonstrate the successful executability and performance measurement of these algorithms on a mobile device operating system and processor, particularly on a smartphone. Open mobile systems such as Android, are most suitable for this task, which is to be performed most efficiently. Furthermore, efficiently implementing an interaction between the algorithm and a graphical user interface (GUI) that runs exclusively on the mobile device is necessary in cases where the project’s goal statement also includes such a task. This paper examines different proposed solutions for porting computer algorithms obtained through rapid development into a GUI-based smartphone Android app and evaluates their feasibilities. Accordingly, the feasible methods are tested and a short success report is given for each tested method.

Keywords: SMARTNAVI, Smartphone, App, Programming languages, Rapid Development, MATLAB, Octave, C/C++, Java, Android, NDK, SDK, Linux, Ubuntu, Emulation, GUI

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Authors: Rodrigo Arnaldo Scarpel

Abstract:

Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

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Authors: C. Paglia, C. Mosca

Abstract:

Synthetic resin floorsare often used in sport infrastructure. These organic materials are often in contact with a bituminous substrate, which in turn is placed on the ground. In this work, the damage of a basket resin field surface was characterized by means of visual inspection, optical microscopy, resin thickness measurements, adhesion strength, water vapor transmission capacity, capillary water adsorption, granulometry of the bituminous conglomerate, the surface properties, and the water ground infiltration speed. The infiltration speed indicates water pemeability. This was due to its composition: clean sand mixed with gravel. Relatively good adhesion was present between the synthetic resin and the bituminous layer. The adhesion resistance of the bituminous layer was relatively low. According to the required bitumoniousasphalt-concrete mixes AC 11 S, the placed material was more porous. Insufficient constipation was present. The spaces values were above the standard limits, while the apparent densities were lower compared to the conventional AC 11 mixtures. The microstructure outlines the high permeability and porosity of the bituminous layer. The synthetic resin wasvapourproof and did not exhibit capillary adsorption. It exhibited a lower thickness as required, and no multiple placing steps were observed. Multiple cavities were detected along with the interface between the bituminous layer and the resin coating with no intermediate layers. The layer for the pore filling in the bituminous surface was not properly applied. The swelling bubbles on the synthetic pavement were caused by the humidity in the bituminous layer. Water or humidity were present prior to the application of the resin, and the effect was worsened by the upward movement of the water from the ground.

Keywords: resin, floor, damage, durability

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Authors: Sujay Kotwale, Ramasubba Reddy M.

Abstract:

Electrocardiogram (ECG) is a non-invasive technique used to study and analyze various heart diseases. Cardiac arrhythmia is a serious heart disease which leads to death of the patients, when left untreated. An early-time detection of cardiac arrhythmia would help the doctors to do proper treatment of the heart. In the past, various algorithms and machine learning (ML) models were used to early-time detection of cardiac arrhythmia, but few of them have achieved better results. In order to improve the performance, this paper implements principal component analysis (PCA) along with XGBoost model. The PCA was implemented to the raw ECG signals which suppress redundancy information and extracted significant features. The obtained significant ECG features were fed into XGBoost model and the performance of the model was evaluated. In order to valid the proposed technique, raw ECG signals obtained from standard MIT-BIH database were employed for the analysis. The result shows that the performance of proposed method is superior to the several state-of-the-arts techniques.

Keywords: cardiac arrhythmia, electrocardiogram, principal component analysis, XGBoost

Procedia PDF Downloads 97